Trace Detection of E. coli O157:H7 Cells by an Au Nanoparticle-Based SERS Aptasensor
Drinking polluted water can cause deadly diseases, and clean water is becoming increasingly scarce in the environment. Various pathogens in water will affect environmental safety and human health, so it is necessary to detect pathogens with sensitivity, specificity, simplicity, and celerity. Here, w...
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Published in | ACS applied nano materials Vol. 6; no. 2; pp. 1386 - 1394 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
American Chemical Society
27.01.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Drinking polluted water can cause deadly diseases, and clean water is becoming increasingly scarce in the environment. Various pathogens in water will affect environmental safety and human health, so it is necessary to detect pathogens with sensitivity, specificity, simplicity, and celerity. Here, we designed a surface-enhanced Raman scattering (SERS) adaptive sensor based on rolling cycle amplification (RCA), in which the introduced Au nanoparticle-based SERS aptasensor could transform the concentration signal of Escherichia coli into a Raman signal, realizing the sensitive analysis of E. coli O157:H7 (E. coli O157:H7). In this strategy, the magnetic beads were modified with double-stranded DNA (dsDNA) to recognize E. coli and initiate RCA. In the presence of E. coli, one strand of dsDNA will recognize it and unchained from dsDNA and the other strand of dsDNA will act as a trigger for RCA. Then, the RCA reaction was initiated. A large number of SERS probes can be attached to RCA products to achieve a strong Raman signal. Under the optimal conditions, we obtained a low limit of detection (LOD = 0.3 CFU/mL) and a wide detection range (102–107 CFU/mL). Also, this SERS aptasensor can complete the detection within 45 min. It can be concluded that this SERS aptasensor has wide application prospects in food safety inspections, environmental monitoring, and clinical diagnosis, as it can provide a fast, sensitive, and one-pot platform for bacterial detection. |
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ISSN: | 2574-0970 2574-0970 |
DOI: | 10.1021/acsanm.2c05031 |